CN105898763B - A kind of directional sensor network coverage optimization method constrained by network lifecycle - Google Patents

A kind of directional sensor network coverage optimization method constrained by network lifecycle Download PDF

Info

Publication number
CN105898763B
CN105898763B CN201610341648.4A CN201610341648A CN105898763B CN 105898763 B CN105898763 B CN 105898763B CN 201610341648 A CN201610341648 A CN 201610341648A CN 105898763 B CN105898763 B CN 105898763B
Authority
CN
China
Prior art keywords
sensor
destination node
node
network
covering
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201610341648.4A
Other languages
Chinese (zh)
Other versions
CN105898763A (en
Inventor
蒋波
蒋一波
汪念华
盛尚浩
梅佳东
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Hangzhou Incandescent Orange Digital Technology Co ltd
Original Assignee
Zhejiang University of Technology ZJUT
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Zhejiang University of Technology ZJUT filed Critical Zhejiang University of Technology ZJUT
Priority to CN201610341648.4A priority Critical patent/CN105898763B/en
Publication of CN105898763A publication Critical patent/CN105898763A/en
Application granted granted Critical
Publication of CN105898763B publication Critical patent/CN105898763B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/18—Network planning tools
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W84/00—Network topologies
    • H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Mobile Radio Communication Systems (AREA)
  • Selective Calling Equipment (AREA)
  • Testing Or Calibration Of Command Recording Devices (AREA)

Abstract

A kind of directional sensor network coverage optimization method constrained by network lifecycle includes the following steps: 1) to initialize；2) it sorts；3) lock onto target node；4) for target TSj, by it is all can be to the working sensor Mode S that it is coveredo,p,qSet CTS is addedj, So,p,qRefer to sensor SoWork calculates the fitness f of each operating mode in the direction p, q-th of power, and the working sensor mode for choosing maximum adaptation degree covers it；5) it updates and judges cycling condition；6) step 3)~5 are repeated) until more covering subsets can not be generated；7) one group of covering subset is exported.It is that cost generates each round covering subset, and then obtains more covering subsets that the present invention, which is consumed under the premise of meeting and covering and require with the smallest wireless network life cycle,.

Description

A kind of directional sensor network coverage optimization method constrained by network lifecycle
Technical field
The present invention relates to a kind of optimization methods of Wireless Sensor Network Coverage Problem, and in particular to one kind is by network life Cycle constraint meets the method that directional sensor network life cycle is maximized under the premise of multiple target covers.
Background technique
Wireless sensor network technology is in recent years because it is in the extensive application of national security, military affairs and environmental monitoring field And it is widely noticed.Wireless sensor network is stored by a large amount of low batteries, the sensor node of low energy consumption forms, these sensor packets Containing main functional modules such as perception, data processing, data transmission.The perception of sensor node is assumed usually in sensor network Range be one using node as the center of circle, using perceived distance as the circle domain of radius.However, due to equipment and environment under reality Constraint, the perception angle of sensor node are restricted, and this kind of sensor is referred to as oriented sensor.Each oriented sensor can To work in several directions, however synchronization can only operate in an operative orientation.Usual oriented sensor only works One power consumption mode, it is contemplated that oriented sensor may have multiple power consumption levels in practical situations, respectively correspond different senses Know radius.
One difficult point of directional sensor network covering: in the case where monitoring all destination nodes at the same time, net is maximized The working time of network.This is a np complete problem, solves the problems, such as that this conventional method is to find covering subset as much as possible, Each covering subset can meet the target coverage of a period of time, when sensor residual energy is unable to satisfy while being covered all Network lifecycle terminates when destination node.
Summary of the invention
In order to overcome the wireless network life cycle of existing directional sensor network coverage mode to consume biggish deficiency, It is that cost generates often that the present invention, which provides a kind of consume under the premise of meeting and covering and require with the smallest wireless network life cycle, One wheel covering subset, and then the directional sensor network covering constrained by network lifecycle for obtaining more covering subsets is excellent Change method.
The technical solution adopted by the present invention to solve the technical problems is:
A kind of directional sensor network coverage optimization method constrained by network lifecycle, includes the following steps:
1) in n sensor node of a 2 dimensional region random placement and m destination node, initializing sensor node is surplus Complementary energy duration set Pl, optional power number K and corresponding the perception radius r and unit time energy consumption c, can perceived direction, initial direction；
2) t moment, t are initially 0, are ranked up to the limitation of network lifecycle to destination node according to destination node, It is stored in TS set, limitation LT of the destination node i to network lifecycleiIt indicates；
3) it enables j=1, j identify the serial number of destination node in TS set, chooses j-th of destination node TS in TS setj, If being capped, j=j+1 chooses next destination node TSj；
4) for target TSj, by it is all can be to the working sensor Mode S that it is coveredo,p,qSet CTS is addedj, So,p,qRefer to sensor SoWork calculates the fitness f of each operating mode in the direction p, q-th of power, chooses maximum adaptation The working sensor mode of degree covers it；
5) dump energy of more new sensor node updates the destination node sequence in TS, if j=n, i.e., all target sections Point is complete capped, generates a covering subset, and t=t+ △ t, all destination nodes become uncovered state again at this time, returns Step 3)；Otherwise, it is returned directly to step 3)；
6) step 3)~5 are repeated) until more covering subsets can not be generated；
7) one group of covering subset is exported.
Further, in the step 2), network lifecycle, which refers to, starts to work from network and covers target complete node, directly It is unable to satisfy to sensor node dump energy and persistently covers all destination nodes within the △ t period；Destination node is to network When the limitation of life cycle refers to that the destination node ambient sensors node is all used to service the destination node, the destination node energy The capped maximum time enough maintained.
Further, in the step 4), the fitness f of each operating mode is calculated according to formula (1):
Pl is sensor residual energy in formula (1), and c is assigned work Mode So,p,qCorresponding power consumption, j are current goal Node TSjRanking, parameter alpha be the operating mode correspond to all targets that the sensor in the circle domain of working radius can cover The ranking near preceding destination node is ranked in node in TS, highest ranks corresponding α=1, the corresponding α=m of minimum ranking, ranking Higher α is lower；And α≤j；Parameter beta is can be covered under the operating mode in addition to TSjOuter also uncovered destination node In, the ranking near preceding destination node is ranked in TS；Parameter beta*It is corresponded in the circle domain of working radius for the operating mode, it should What sensor can cover removes TSjIn outer also uncovered destination node, ranking is near preceding destination node in TS Ranking, j < β≤β*), Pl is sensor residual energy.
Technical concept of the invention are as follows: for maximization life of the directional sensor network in the case where meeting certain covering and requiring Periodic problem, a kind of typical solution are exactly to find out covering subset as much as possible, and each covering subset can meet Given covering requirement.The it is proposed of the invention is arranged according to limited degree of the destination node to network lifecycle Sequence, and retain in the selection of sensor node that may to cover more common-denominator target node (bigger to network limited degree as far as possible Destination node) sensor node, thus meet covering require under the premise of, with the smallest wireless network life cycle consumption Each round is generated for cost and covers subset, and then obtains more covering subsets.
Overlay area destination node is ranked up the limitation of directional sensor network life cycle according to it first, connects Destination node is successively chosen according to above-mentioned sequence, and choose maximum adaptation degree working sensor mode and it covered.Often A sensor is enabled, the dump energy of more new sensor node recalculates and adjust the sequence of destination node.Until all Destination node it is capped, generate a covering subset at this time.It steps be repeated alternatively until the dump energy of all the sensors More covering subsets can not be generated.Export one group of covering subset；
Beneficial effects of the present invention are mainly manifested in: with the smallest wireless network life under the premise of meeting covering and requiring Period consumption is that cost generates each round covering subset, and then obtains more covering subsets.
Detailed description of the invention
Fig. 1 is directional sensing model schematic diagram, and example model works in 2 power grades, and 3 operative orientations are (as shown in figure 1 It is expressed as d1,d2,d3), each operative orientation corresponds to the working range (being here 120 °) of θ angle.
Fig. 2 is the flow chart of the directional sensor network coverage optimization method constrained by network lifecycle；
Specific embodiment
The invention will be further described below in conjunction with the accompanying drawings.
Referring to Figures 1 and 2, a kind of directional sensor network coverage optimization method constrained by network lifecycle, including Following steps:
1) is initialized
In n sensor node of a 2 dimensional region random placement and m destination node, initializing sensor node is remaining Energy aggregation Pl, optional power number K and corresponding the perception radius r and unit time energy consumption c, can perceived direction, initial direction.
2) sorts
T moment (t is initially 0) is ranked up the limitation of network lifecycle to destination node according to destination node (note: network lifecycle, which refers to, starts to work from network and covers target complete node, until sensor node dump energy can not Satisfaction persistently covers all destination nodes within the △ t period；Destination node refers to the target section to the limitation of network lifecycle Point ambient sensors node is when being all used to service the destination node, when the capped maximum which is able to maintain that Between), it is stored in TS set.Limitation LT of the destination node i to network lifecycleiIndicate
3) lock onto target node
J=1, j is enabled to identify the serial number of destination node in TS set.Choose j-th of destination node TS in TS setjIf It has been be capped that, then j=j+1, chosen next destination node TSj。
4) coverage goal node
For target TSj(note: TS set in j-th of destination node), by it is all can be to the sensor work that it is covered Operation mode So,p,q(note: sensor SoWork is in the direction p, q-th of power) set CTS is addedj, calculated according to formula (1) each The fitness f of operating mode, the working sensor mode for choosing maximum adaptation degree cover it.
Pl is sensor residual energy in formula (1), and c is assigned work Mode So,p,qCorresponding power consumption, j are current goal Node TSjRanking, parameter alpha is that the operating mode corresponds in the circle domain of working radius and (relaxes the corresponding sense of the operating mode Know angle, enable it for a round domain) (including the TS that covers of the sensorjIt is ranked in TS in all destination nodes inside) Near the ranking of preceding destination node, (note: highest ranks corresponding α=1, and it is lower to rank higher α by the corresponding α=m of minimum ranking；And α ≤j)；Parameter beta is can be covered under the operating mode in addition to TSjIn outer also uncovered destination node, arranged in TS Ranking of the position near preceding destination node；Parameter beta*It is corresponded in the circle domain of working radius for the operating mode and (relaxes the work The corresponding perception angle of mode makes its round domain), what which can cover removes TSjOuter also uncovered mesh It marks in node, the ranking (note: j < β≤β near preceding destination node is ranked in TS*).Pl is sensor residual energy, and m is Destination node number, n are sensor node quantity.
5) updates and judges cycling condition
The dump energy of more new sensor node updates the destination node sequence in TS, if j=n (i.e. all destination nodes It is complete capped), a covering subset is generated, t=t+ △ t, all destination nodes become uncovered state again at this time, return to step It is rapid 3)；Otherwise, being returned directly to step 3) (note: not enabling j=j+1, return step 3 here), j is still assigned 1 afterwards, the reason is that examining Consider the possibility that ranking has adjustment).
6) finds more covering subsets
Repeat step 3)~5) until more covering subsets can not be generated.
7) is exported
Finally, one group of covering subset of output.
A kind of typical sensor model of directional sensing model of the invention as sensor network, the perception model of corresponding node Enclose be one using node as the center of circle, radius be its perceived distance fan-shaped region.The sensor that the present invention uses is that more power pass Sensor, different capacity have corresponding energy consumption and the perception radius.Sensor sensor model such as Fig. 1 that the present invention uses.
Fig. 1 illustrates one and can work in the oriented sensor of 2 power grades, 3 operative orientations.Oriented sensor can To work in several different directions, the corresponding perception angle of these operative orientations is not overlapped, and is altogether a round domain.If passing Sensor has K power consumption mode, corresponding K power consumption and the perception radius.Destination node is not subjected to displacement after generating at random.
Above-described implementation is only that preferred embodiments of the present invention will be described, not to the scope of the present invention into Row limits, and without departing from the spirit of the design of the present invention, those of ordinary skill in the art do technical solution of the present invention Various changes and improvements out should all be fallen into the protection scope that claims of the present invention determines.

Claims (3)

1. a kind of directional sensor network coverage optimization method constrained by network lifecycle, it is characterised in that: including as follows Step:
1) in n sensor node of a 2 dimensional region random placement and m destination node, initializing sensor node residual energy Duration set Pl, optional power number K and corresponding the perception radius r and unit time energy consumption c, can perceived direction, initial direction；
2) t moment, t are initially 0, are ranked up to the limitation of network lifecycle to destination node according to destination node, storage In TS set, limitation LT of the destination node i to network lifecycleiIt indicates；
3) it enables j=1, j identify the serial number of destination node in TS set, chooses j-th of destination node TS in TS setjIf by Covering, then j=j+1, chooses next destination node TSj；
4) for target TSj, by it is all can be to the working sensor Mode S that it is coveredo,p,qSet CTS is addedj, So,p,qIt is Refer to sensor SoWork calculates the fitness f of each operating mode in the direction p, q-th of power, chooses the biography of maximum adaptation degree Sense device working mode covers it；
5) dump energy of more new sensor node updates the destination node sequence in TS, if j=m, i.e., all destination nodes are complete It is capped, a covering subset is generated, t=t+ △ t, all destination nodes become uncovered state, return step again at this time 3)；Otherwise, it is returned directly to step 3)；
6) step 3)~5 are repeated) until more covering subsets can not be generated；
7) one group of covering subset is exported.
2. a kind of directional sensor network coverage optimization method constrained by network lifecycle as described in claim 1, Be characterized in that: in the step 2), network lifecycle, which refers to, starts to work from network and covers target complete node, until sensing Device residue energy of node, which is unable to satisfy, persistently covers all destination nodes within the △ t period；Destination node is to network life week When the limitation of phase refers to that the destination node ambient sensors node is all used to service the destination node, which is able to maintain that Capped maximum time.
3. a kind of directional sensor network coverage optimization method constrained by network lifecycle as claimed in claim 1 or 2, It is characterized by: calculating the fitness f of each operating mode according to formula (1) in the step 4):
Pl is sensor residual energy in formula (1), and c is assigned work Mode So,p,qCorresponding power consumption, j are current target node TSjRanking, parameter alpha be the operating mode correspond to all destination nodes that the sensor in the circle domain of working radius can cover In rank ranking near preceding destination node in TS, highest ranks corresponding α=1, the corresponding α=m of minimum ranking, and ranking is higher α is lower；And α≤j；Parameter beta is can be covered under the operating mode in addition to TSjIn outer also uncovered destination node, The ranking near preceding destination node is ranked in TS；Parameter beta*It is corresponded in the circle domain of working radius for the operating mode, the biography What sensor can cover removes TSjIn outer also uncovered destination node, the row near preceding destination node is ranked in TS Position, j < β≤β*。
CN201610341648.4A 2016-05-20 2016-05-20 A kind of directional sensor network coverage optimization method constrained by network lifecycle Active CN105898763B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201610341648.4A CN105898763B (en) 2016-05-20 2016-05-20 A kind of directional sensor network coverage optimization method constrained by network lifecycle

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201610341648.4A CN105898763B (en) 2016-05-20 2016-05-20 A kind of directional sensor network coverage optimization method constrained by network lifecycle

Publications (2)

Publication Number Publication Date
CN105898763A CN105898763A (en) 2016-08-24
CN105898763B true CN105898763B (en) 2019-04-23

Family

ID=56716503

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201610341648.4A Active CN105898763B (en) 2016-05-20 2016-05-20 A kind of directional sensor network coverage optimization method constrained by network lifecycle

Country Status (1)

Country Link
CN (1) CN105898763B (en)

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102843743A (en) * 2012-07-18 2012-12-26 南京邮电大学 Hierarchical routing method of wireless sensor network based on flora foraging optimization algorithm

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2134034A1 (en) * 2008-06-10 2009-12-16 Fujitsu Limited Improvements in wireless sensor networks

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102843743A (en) * 2012-07-18 2012-12-26 南京邮电大学 Hierarchical routing method of wireless sensor network based on flora foraging optimization algorithm

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
Optimization for K Level Coverage of Video WSN Based on Number Restriction;Jiang,YB;《International Conference on Computer Science and Communication Engineering (CSCE)》;20150613;526-531 *
视频传感器网络中多路径K级覆盖动态优化算法;蒋一波等;《仪器仪表学报》;20150415(第04期);830-840 *

Also Published As

Publication number Publication date
CN105898763A (en) 2016-08-24

Similar Documents

Publication Publication Date Title
Adu-Manu et al. Energy-harvesting wireless sensor networks (EH-WSNs) A review
Mabon et al. The Smaller the Better: Designing Solar Energy Harvesting Sensor Nodes for Long‐Range Monitoring
CN110620611B (en) Cooperative spectrum sensing method based on GEO and LEO double-layer satellite network
Xiong et al. A two-phase lifetime-enhancing method for hybrid energy-harvesting wireless sensor network
CN106056269A (en) NanoSat satellite house-keeping health management system based on Bayes network model
CN112637860B (en) Three-dimensional wireless sensor network coverage method and system
Zhang et al. A preliminary study on lifetime maximization in clustered wireless sensor networks with energy harvesting nodes
Basilico et al. Coordinating multiple defensive resources in patrolling games with alarm systems
CN105898763B (en) A kind of directional sensor network coverage optimization method constrained by network lifecycle
Charoenchaiprakit et al. Optimal data transfer of SEH-WSN node via MDP based on duty cycle and battery energy
Martin et al. Centralized MPPT controller system of PV modules by a wireless sensor network
Castillo-Atoche et al. An energy-saving data statistics-driven management technique for bio-powered indoor wireless sensor nodes
US20170195414A1 (en) Compact, Componentized Hardware Architecture and Reference Platform Family for Low-Power, Low-Cost, High-Fidelity In Situ Sensing
CN109474904B (en) Wireless sensor network compressed data collection method considering energy consumption and coverage
CN107181270B (en) A kind of more energy storage flexibilities inhibit the Stochastic Dynamic Programming Method of wind-powered electricity generation
CN105093978A (en) Sensor apparatus and associated methods
Rioual et al. Reinforcement-learning approach guidelines for energy management
Yadav Optimal ATC enhancement model: analysis of the effect of thyristor-controlled series compensation
CN107196347A (en) A kind of electric adjustment method and device
Belghith et al. Extending the network lifetime of wireless sensor networks using fuzzy logic
Liu et al. A moving algorithm for non-uniform deployment in mobile sensor networks
CN105578485B (en) A kind of wireless sensor network linear programming method
Kaur et al. Lifetime enhancement of wireless sensor network using solar energy harvesting technique
CN109688598A (en) Complex grid distributed data acquisition system and transmission optimization method based on WSAN
Onwunali et al. Modelling of the energy level and outage analysis for battery-powered IoT Sensor node with solar energy harvester

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant
TR01 Transfer of patent right
TR01 Transfer of patent right

Effective date of registration: 20230717

Address after: 310000 rooms 702 and 703, Yuesheng International Center, ningwei street, Xiaoshan District, Hangzhou City, Zhejiang Province

Patentee after: Hangzhou Incandescent Orange Digital Technology Co.,Ltd.

Address before: The city Zhaohui six districts Chao Wang Road Hangzhou City, Zhejiang province 310014 18

Patentee before: JIANG University OF TECHNOLOGY